ArticleFrontiers in rehabilitation sciences2026
Using AI in healthcare education: a rapid review and commentary.
Article in Frontiers in rehabilitation sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- The Challenges of AI Applications in Health Care: Qualitative Study.Journal of medical Internet research · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is rapidly transforming healthcare and rehabilitation education, offering new pathways for personalized learning, adaptive assessment, and simulation-based training. This paper provides a rapid review and commentary on current research exploring AI's integration into healthcare curricula, highlighting its potential to enhance competency development, critical thinking, and learner engagement. Evidence shows that AI can enrich educational experiences by tailoring instruction to individual needs, facilitating clinical reasoning, and reducing the cognitive and logistical burdens faced by graduate students who balance academics with professional and personal responsibilities. Yet, the increasing reliance on AI also introduces ethical, cultural, and pedagogical challenges, including algorithmic bias, data privacy concerns, inequitable access to technology, and the risk of diminishing independent judgment. Within rehabilitation education, additional issues arise related to patient confidentiality, assessment authenticity, and the unauthorized use of educators' intellectual property. The findings emphasize that successful integration of AI in healthcare education depends on proactive strategies that uphold ethical practice, equity, and reflective learning. By embedding AI literacy, cultural humility, and clear ethical guardrails into curricula, educators can ensure that technology complements-rather than compromises-the humanistic and critical dimensions of healthcare practice.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.